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antideploy-mcp

Official
by antideploy

Store variables from a local .env file

set_env_from_file
Destructive

Reads named variables from a .env file and stores them for the application so values bypass the conversation; only listed names are sent. Redeploy to apply them.

Instructions

Read the named variables out of a .env file in the project directory and store them for the application, so the values go from the file to Antideploy and never through this conversation. Only the names you list are sent. Names the platform fills in itself (the database, storage, sign-in and email variables, the application's own address and generated signing secrets) are refused with the reason, and so are empty values and template placeholders like your-key-here. The result names what was stored and what was skipped, never a value. Redeploy afterwards for the running app to pick them up.

Input Schema

NameRequiredDescriptionDefault
fileNoA .env file inside the project directory. Default .env.
namesYesThe variable names to store, such as STRIPE_SECRET_KEY.
directoryNoThe project folder. Defaults to this server's working directory.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the destructiveHint/openWorldHint annotations, the description discloses real behavioral detail: only listed names are sent, platform-reserved variables (DB, storage, auth, email, app address, signing secrets) are refused with a reason, empty values and placeholders like your-key-here are skipped, and results report names only, never values. That is exactly the context an agent needs before invoking a mutation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and mechanism, then the refusal rules, then the redeploy note. It is a bit long, but each sentence adds operative information (refusals, value confidentiality, next step) rather than padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description explains what the result contains (stored vs skipped, no values) and the required follow-up redeploy, covering the gaps a mutation tool with no output schema would otherwise leave.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and each parameter is documented, so the schema carries parameter meaning. The description adds only that 'only the names you list are sent' and that reserved names are refused, which is mild added value over a fully covered schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names the specific action (read named variables from a .env file and store them) and the distinctive mechanism (values go file→Antideploy, never through the conversation), which clearly separates it from set_env and list_env. An agent can route to it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies the selection condition strongly — use this when values live in a local .env file rather than being passed in chat — and gives the follow-up step (redeploy for the running app to pick changes up). It does not explicitly name set_env as the alternative for in-conversation values, so it stops short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.